The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project that
includes characterization of chemical and physical attributes of aerosols
from filter samples collected worldwide. This paper discusses the
ongoing efforts of SPARTAN to define and quantify major ions and trace
metals found in fine particulate matter (PM2.5). Our methods infer the
spatial and temporal variability of PM2.5 in a cost-effective manner.
Gravimetrically weighed filters represent multi-day averages of PM2.5,
with a collocated nephelometer sampling air continuously. SPARTAN
instruments are paired with AErosol RObotic NETwork (AERONET) sun
photometers to better understand the relationship between ground-level
PM2.5 and columnar aerosol optical depth (AOD).

The expected water contribution to aerosols is calculated via the
hygroscopicity parameter κv for each filter. Mean aggregate
values ranged from 0.15 (Ilorin) to 0.28 (Rehovot). The all-site parameter
mean is 0.20 ± 0.04. Chemical composition and water retention in each
filter measurement allows inference of hourly PM2.5 at 35 % relative
humidity by merging with nephelometer measurements. These hourly PM2.5
estimates compare favourably with a beta attenuation monitor (MetOne) at the
nearby US embassy in Beijing, with a coefficient of variation r2= 0.67 (n= 3167), compared to r2=0.62 when κv was
not considered. SPARTAN continues to provide an open-access database of
PM2.5 compositional filter information and hourly mass collected from a
global federation of instruments.

Introduction

Fine particulate matter with a median aerodynamic diameter less than or
equal to 2.5 µm (PM2.5) is a robust indicator of premature
mortality (Chen et al., 2008; Laden
et al., 2006). Research on long-term exposure to ambient PM2.5 has
documented serious adverse health effects, including increased mortality
from chronic cardiovascular disease, respiratory disease, and lung cancer
(WHO, 2005). Outdoor fine particulate matter (PM2.5) is
recognized as a significant air pollutant, with an air quality guideline set
by the WHO at 10 µg m-3 annual average (WHO, 2006).
Many regions of the world far exceed these long-term recommendations
(Brauer et al., 2015; van Donkelaar et al., 2015), and the impact on health is
substantial. The 2013 Global Burden of Disease estimated that outdoor
PM2.5 caused 2.9 million deaths (3 % of all deaths) and 70 million
years of lost healthy life on a global scale
(Forouzanfar et al., 2015). Atmospheric aerosol is
also the most uncertain agent contributing to radiative forcing of climate
change (IPCC, 2013). Aerosol mass and composition
also play a critical role in atmospheric visibility (Malm et al., 1994).
Additional observations are needed to improve the concentration estimates
for PM2.5 as a global risk factor, and to better understand the
chemical components and sources contributing to its formation.

No global PM2.5 protocol exists for relative humidity (RH) filter
equilibration. The U.S. EPA measurements are between 30 and 40 % RH, European
measurements are below 50 % RH, and different protocols exist elsewhere.
Ambient humidity affects the relationship of dry PM2.5 with satellite
observations of aerosol optical depth. Aerosol water also influences the
relationship between dry PM2.5 and aerosol scatter. A large body of
literature has examined the relationship of aerosol composition with
hygroscopicity (e.g. IMPROVE (Hand et al., 2012; IMPROVE, 2015), Chemical
Species Network (CSN) (Chu, 2004; USEPA, 2015), ISORROPIA
(Fountoukis and Nenes, 2007), and Aerosol Inorganic Model
(AIM) (Wexler and Clegg, 2002)). More recently, Petters and Kreidenweis (2007,
2008, 2013) have developed κ-Kohler theory, which assigns individual
hygroscopicity parameters κ to all major components, from insoluble
crustal materials to sea salt. Mixed values can then be weighted by local
aerosol composition.

Ground-based observations of PM2.5 have insufficient coverage at the
global scale to provide assessment of long-term human exposure. Satellite
remote sensing offers a promising means of providing an extended temporal
record to estimate population exposure to PM2.5 on a global scale, and
especially for areas with limited ground-level PM2.5 measurements
(Brauer et al., 2015; van Donkelaar et al., 2015). Even in areas where
monitor density is high, satellite-based estimates provide additional useful
information on spatial and temporal patterns in air pollution (Kloog et al.,
2011, 2013; Lee et al., 2012). However, there are outstanding questions about
the accuracy and precision with which ground-level aerosol mass
concentrations can be inferred from satellite remote sensing. Standardized
PM2.5 measurements, collocated with ground-based measurements of aerosol
optical depth, are needed to evaluate and improve PM2.5 estimates from
satellite remote sensing. To meet these sampling needs, the ground-based
network SPARTAN (Surface PARTiculate mAtter Network) is designed to evaluate
and enhance satellite-based estimates of PM2.5 by measuring fine-particle
aerosol concentrations and composition continuously over multi-year
periods at sites where aerosol optical depth is also measured (Holben et al.,
1998; Snider et al., 2015). The network includes air filter sampling and
nephelometers that together provide long-term and hourly PM2.5 estimates
at low RH (35 %).

We discuss the ongoing efforts of the SPARTAN project to quantify major ions
and trace metals found in aerosols worldwide. Section 2 describes the
methodology used to infer PM2.5 composition. Section 3 defines
categories of aerosol types (crustal and residual material, equivalent black
carbon, ammonium nitrate, ammoniated sulfate, sea salt, and trace metal
oxides) as a function of specific chemical species. Section 4 describes the
implementation of sub-saturated κ-Kohler theory to estimate aerosol
water content based on aerosol compositional information. Section 5 compares
relative aerosol composition with that reported in available literature, and
assesses the general consistency of our findings across all sites. Section 6
evaluates hourly PM2.5 estimates (35 % RH) at Beijing with a beta
attenuation monitor at the US embassy.

Overview of methodology

SPARTAN has been collecting PM2.5 on PTFE filters for at least 2
months, across 13 SPARTAN sites, between 2013 and 2016, with an average
period of 12 months per site. Snider et al. (2015) provide an overview of the
SPARTAN PM observation network, the cost-effective sampling methods employed
and post-sampling instrumental methods of analysis. Each site utilizes a
combination of continuous monitoring by nephelometry and mass concentration
via filter-based sampling. Nephelometer scatter is averaged to hourly
intervals at three wavelengths (457, 520, 634 nm), and converted to 550 nm
via a fitted Angstrom exponent. Total scatter is proportional to PM2.5
mass and volume (Chow et al., 2006). Hence, we provide dry (35 % RH) hourly
PM2.5 estimates by combining scatter at 550 nm at ambient RH with filter
mass and chemical composition information used to determine water content as
described below.

Briefly, filter-based measurements are collected with an AirPhoton SS4i
automated air sampler. Each sampler houses a removable filter cartridge that
protects seven sequentially active 25 mm diameter filters, plus a field
blank. Air samples first pass through a bug screen and then a greased
impactor plate to remove particles larger than 10 µm in diameter.
Aerosols are collected in sequence on a preweighed Nuclepore filter membrane
(8 µm, SPI) that removes coarse-mode aerosols with diameters from
2.5 to 10 µm in diameter (PMc), while fine aerosols
(PM2.5) are then collected on pre-weighed PTFE filters (2 µm,
SKC). For each filter, sampling is timed at regular, staggered 24 h
intervals throughout a 9-day period. Sampling ends for each filter at
09:00 LT when temperatures are low, to reduce loss of semi-volatile components. As
described by Snider et al. (2015), loss rates of ammonium nitrate during
passive air flow were an order of magnitude less than during active air flow.
Thus, the sampling protocol is designed to actively sample for one diurnal
cycle and to avoid daytime sampling after collecting nighttime PM. Following
the IMPROVE protocol
(Hand and Malm, 2006), filters are transported at room
temperature in sealed containers between measurement sites and the central
SPARTAN laboratory at Dalhousie University, where analysis is conducted.
Site locations are designed to sample under a variety of conditions,
including biomass burning (e.g. west Africa and South America), biofuel
emissions (e.g. south Asia), monsoonal conditions (e.g. west Africa and
southeast Asia), suspended mineral dust (e.g. west Africa and the Middle
East) and urban crustal material. Each SPARTAN site provides a
representative example of local and regional conditions in highly populated
areas. Site selection prioritizes under-represented, globally dispersed,
population-dense regions; no SPARTAN sites exist yet in Europe. The sites of
Atlanta and Mammoth Cave are included for instrument inter-comparison
purposes with other networks.

Filter weighing

Filters (PTFE, capillary) are both pre and post-weighed in triplicate using a
Sartorius Ultramicro balance with 0.1 µg precision. Gravimetric
weighing is performed in a cleanroom facility at 35 ± 5 % RH and
20–23 ∘C. A total of 497 quality-controlled filters have been
weighed across all SPARTAN sites. The median collected material on sampled
filters, as well as the lower and upper quintiles (in parentheses), are 72
(42, 131) µg for Teflon and 90 (44, 154) µg for
Nuclepore. The combined uncertainty (±2σ) of quality-assured
single-filter PM mass measurements is ±4.0 µg. Time-integrated
flow rates at ambient air pressure and temperature are used to define the
sampled volume for aerosol concentrations reported inµg m-3.
These filters are subsequently analysed for water-soluble ions, trace metals,
and surface reflectance to obtain equivalent black carbon.

Equivalent black carbon (EBC)

We define the equivalent black carbon (EBC) as the black carbon content of
PTFE filters derived via surface reflectance R using the Diffusion Systems
EEL 43M smoke stain reflectometer (Quincey et al., 2009) as further discussed
in Sect. 4.6. We use the term “equivalent black carbon” following the
recommendation of Petzold et al. (2013) for data derived from optical
absorption methods.

Trace metals

To maximize the information extracted from the filters, each one is cut in
half with a ceramic blade following approaches similar to Zhang et al. (2013)
and Gibson et al. (2009). One filter half is analysed for crustal components
Mg, Fe, and Al as well as trace elements Zn, V, Ni, Cu, As, Se, Ag, Cd, Sb,
Ba, Ce, and Pb. We first digest this filter half by adding it to 3.0 mL of
7 % trace-metal-grade nitric acid, similar to Fang et al. (2015). The
acid–filter combination is boiled at 97 ∘C for 2 h, and the liquid extract
is submitted for quantitative analysis via inductively coupled plasma mass
spectrometry (ICP-MS, Thermo Scientific X-Series 2), and follows standardized
methodology as in Rice et al. (2012). The ICP-MS analysis is quantified via
five concentrations (25, 50, 100, 250, and 500 µg L-1) of a
25-element acidified stock solution. Three reference metal ions (45Sc,
115In, and 159Tb) are also used for atomic mass calibration. All
ion mass signals are measured in triplicate, and the mean signal value is
used for elemental quantification.

Water-soluble ions

Water-soluble ions NO3-, SO42-,
NH4+, K+Na+ are detected using the second filter
half. The filter is spiked with 120 µL of isopropyl alcohol and
immersed in 2.9 mL of 18 MΩ Milli-Q water. Filters and liquid
extracts are sonicated together for 25 min before being passed through a
0.45 µm membrane filter to remove larger matrix components.
Extractions are analysed by ion chromatography (IC) via a Thermo Dionex
ICS-1100 instrument (anions) and a Thermo Dionex ICS-1000 (cations)
instrument (Gibson et al., 2013a, b).

Section 2 defined the methodology of basic physical and chemical properties
obtained in SPARTAN filters. Section 3 describes the chemical definitions
used to infer each chemical component as discussed in turn below. Table 1
contains a summary of equations and accompanying references used to quantify
SPARTAN PM2.5 chemical composition.

Sea salt (SS)

We take 10 % of [Al] to be associated with Na and remove this crustal
sodium component (Remoundaki et al., 2013). Sea salt is then represented as
2.54[Na+]ss to account for the associated [Cl-] (Malm et
al., 1994).

Ammonium nitrate (ANO3)

We treat all nitrate as neutralized by ammonium as NH4NO3. The
corresponding mass of ANO3 is a 1:1 molar ratio of
NH4 : NO3, or 1.29[NO3-] based on molecular weight.

Sodium sulfate (Na2SO4)

Sodium sulfate is treated as a fraction of measured sodium,
0.18[Na+]SS (Henning et al., 2003); however, it contributes
negligibly to total aerosol mass (< 0.1 %) at all sites.

Ammoniated sulfate (ASO4)

Ammonium not associated with nitrate and sulfate not associated with
sodium are assumed to be associated as a mixture of NH4HSO4 and
(NH4)2SO4.

Crustal material (CM)

Crustal material consists of resuspended road dust, desert dust, soil, and
sand. Following the elemental composition of natural desert dusts by Wang
(2015), we generalize that natural CM is approximately 10 × [Al +
Fe + Mg]. Aluminum, iron, and magnesium are chosen due to their
collectively consistent composition in natural mineral dust and frequency
above detection limit (> 95 %). Silicon is not available. Titanium was
found not to contribute significantly (< 1 %) to CM mass.

Equivalent black carbon (EBC)

The amount of EBC carbon (µg) is logarithmically related to
concentration, as determined by relative surface reflectance R/R0. For a
given exposed filter area, absorption cross section and light path,
reflectance is related to concentration via
EBC=-AqvlnRR0,
where v is volume of air (0.9–5.8 m3), A is the filter surface
area (3.1 cm2), and q is the product of the effective reflectivity
path p and mass-specific absorption cross section σSSR
(cm2µg-1). The absorption coefficient
σSSR used here is 0.06 cm2µg-1 based on
prior literature (Barnard et al., 2008; Bond and Bergstrom, 2006), adjusted
to the 620 nm detection peak of the SSR. The effective light path p here
is taken to be 1.5 for our thick PTFE filters (e.g. Taha et al., 2007). We
treat water uptake by EBC as negligible.

Trace elemental oxides (TEO)

Trace elemental oxides are the summation of estimated oxide mass for trace
elements as measured by ICP-MS, and make up a negligible portion of total
mass (< 1 %). We include these concentrations for completeness. Water
uptake by TEO is treated as negligible.

Particle-bound water (PBW) associated with inorganics

We estimate the water-mass uptake for the inorganic chemical components of
sea salt (SS), ammonium nitrate (ANO3), and ammoniated sulfate
(ASO4). The mass of particle-bound water (PBW) associated with chemical
component X is
PBWX=[X]κm,XRH100-RH.
The total mass of inorganic (IN) PBW is then
PBWIN=∑XPBWX.

Residual matter (RM)

Residual matter, which is treated as mainly organics, is estimated by
subtracting dry inorganic mass (IN) and its associated water (referenced to
our weighing conditions of 35 ± 5 % RH) from total PM2.5 mass:RM35%=PM2.5,35%-[IN]-[PBWIN].

Negative RM35% values are retained if reconstructed inorganic mass at
35 % RH exceeds total PM2.5 by less than 10 %, otherwise values are
flagged and excluded from the mass average. Negative values occur, on
average, 2 % of the time. Water-free RM (0 % RH) is estimated by
subtracting organic-associated PBW using an estimated hygroscopic parameter
κm,RM=0.1 as discussed in Sect. 4.

Aerosol hygroscopicity

We apply the single-parameter measure of aerosol hygroscopicity (κ)
developed by Petters and Kreidenweis (2007, 2008, 2013) to represent the
contribution of water uptake by individual components. The κ
parameter is defined from 0 (insoluble materials) to greater than 1 for sea
salt. Although initially developed for supersaturated CCN conditions,
hygroscopic parameters κ have been more recently used in
sub-saturated conditions
(Chang et al., 2010; Dusek et al., 2011; Giordano et al., 2013; Hersey et al.,
2013). For particle diameters that dominate the mass fraction of PM2.5
(larger than 50 nm), the difference in κ between CCN and
sub-saturated aerosols is small (Dusek et al., 2011). The water retention of
internal mixtures of aerosol components is often predicted within
experimental error (Kreidenweis et al., 2008). Aged, polarized organic
material, which is a major component of PM2.5, shows comparable growth
factors both in super- and sub-saturated regions (Rickards et al., 2013).

The volume hygroscopicity parameter κv is defined as a
function of particle volume V and water activity aw:
1aw=1+κvVdVw,
where Vd and Vw are the dry particulate matter and
water volumes, respectively. To a first-order approximation
aw= RH/100. Aerosol volume growth is related via κ and
RH by defining fv(RH) as the humidity-dependent ratio of wet and
dry aerosol volume:
fvRH≡VtotVd=Vd+VwVd=a+κvRH100-RH.
Combining the previous equations and relating to a diameter D growth factor
(GF ≡D/Dd) yields
GF=a+κvRH100-RH1/3,
where a=1, except for sea salt, as discussed in Sect. 3.1. Reliable
estimates of κv are available for individual
components (cf. Table 2).

Figure 1 shows the hygroscopic growth for inorganics. The κv
value of 0.51 for ammonium sulfate best matches the AIM model over RH =
10–90 % and is similar to the GF-derived κv= 0.53
estimated by Petters and Kreidenweis (2007). The κv value
for ammonium bisulfate is similar to the κv value of
ammonium sulfate, which is adopted here for ASO4. Our AIM-derived
ammonium nitrate growth curve is smaller than ammonium sulfate, at
κv= 0.41. Empirically, both ammonium compounds share the
same GF = 1.6 at RH = 85 % (Sorooshian et al., 2008), however,
ANO3 is less hygroscopic at lower RH.

Sea salt accounts for a small fraction of aerosol mass over land, however, its
hydrophilic nature makes it significant for water retention. A 1:1 volume
ratio with water as RH approaches 0 %
(Kreidenweis et al., 2008) yields a=2 (Eqs. 2 and
3). A hygroscopic constant κv= 1.5 then best fits AIM from
the deliquescence point up to 90 % RH.

Identifying a representative organic hygroscopic parameter is challenging, as
many volume growth curves are available based on a variety of laboratory
experiments and field campaigns. Organic composition varies by site, and by
season. The Appendix Table Al contains a collection of hygroscopic parameters
from the literature. Values for κv,OM range from 0 to 0.2. We
choose a single κv,OM value based on the oxygen/carbon ratio
(O : C), which is a function of oxidation, hence age of the organics.
Generally O : C ratios are between 0.2 and 0.8 in urban environments
(Rickards et al., 2013). We select an O : C ratio of 0.5
to represent the populated nature of SPARTAN sites (e.g. Robinson et al.,
2013). This corresponds to an organic parameter of κv,OM=0.1
for a variety of organic mixtures (Jimenez et al., 2009).

Aerosol water in multi-component systems

Mass-based hygroscopic water uptake κm is more convenient
than κv to estimate water retention in gravimetric analysis.
The parameters κv and κm are related by
water-normalized density, κm,X=κv,X/ρX. Table 2
contains κv values identified for major aerosol chemical
components and densities. For a multi-component system we estimate aerosol
water mass using a mass-weighted combination of κm values:
κm,tot=1M∑XmXκm,X.
Mass calculations are used to determine residual aerosol mass as described in
Sect. 3.9. Estimates of total water uptake by volume are applied to aerosol
light scatter in Sect. 5. The volume parameter κv,tot is similarly
determined by a linear combination of volume-weighted components X (e.g.
Bezantakos et al., 2013):
κv,tot=1V∑XvXκv,X.

The hygroscopic growth of ASO4 and organic mixtures are treated as
linear combinations of pure compounds (Robinson et al., 2013). Errors in
aerosol water uptake are less significant in mixtures than for individual
species due to dilution effects (Kreidenweis et al., 2008). For ambient
aerosols, empirically measured κv,tot usually lies between
0.14 and 0.39 (Carrico et al., 2010).

Sources of uncertainty

Uncertainty in atmospheric PM2.5 concentrations can be separated into
air volume and PM2.5 mass. We estimated total flow volume variance to be
±10 %, while 2σ pre- and post-gravimetric mass measurement
varied by a combined ± 4 µg. Characterization of hourly
PM2.5 uncertainties can be found in Appendix A2.

Of concern is the loss of semi-volatiles after sampling. In the laboratory
semi-volatile loss is inhibited by storing filters in closed containers. As
discussed in Sect. 2, the sampling protocol is designed to minimize
semi-volatile loss. We tested the retention of semi-volatile material in the
field by examining the trend in PM2.5 and ANO3 mass from the first
filter sampled (54-day residence time in instrument) through the last filter
sampled (negligible residence time in instrument). Statistically
insignificant trends were found for both PM2.5
(-0.09 ± 0.46 µg m-3 position-1) and ANO3
(0.06 ± 0.15 µg m-3 position-1), providing confidence in
retention of semi-volatiles on filters in the cartridge.

Other uncertainties include absolute equivalent black carbon mass due to the
reflectivity path p (±30 %) and absorption cross section σ
(±30 %), which combine to (in quadrature) ±42 %. Trace metal
recovery yields were tested using a sequential second digestion with 20 %
nitric acid. Each acid-digested element was quantified by five dilutions of a
25-element standard (25–500 ppb), plus three internal calibration metals
(Sc, In, Tb). The elemental comparison of crustal materials varies regionally
(Wang, 2015), which contributes to CM uncertainty of ±30 % based on Al,
Fe, and Mg composition. Recovery of individual water-soluble elements was
determined through five-point anion and cation standards curves each with
r2>98 % and < 10 % mass uncertainty for most elements at
environmentally relevant concentrations, including sulfate, nitrate, and
ammonium. Based on lab filter spike tests, water-soluble ion extractions show
> 95 % extraction efficiency. Uncertainties of water-soluble ion yields
are generally ±5 %, except when close to the limit of detection
(approximately 0.1 µg m-3, depending on filter sampling
duration). Errors in the component values affect our estimate of
κv, which will affect the inferred aerosol water. Network
evaluation is an ongoing task that will continue over time.

Mass speciation resultsOverview of PM2.5 mass speciation

PM2.5 composition and water content (µg m-3) at each
SPARTAN location.

There is significant variation of relative and absolute speciation from these
long-term averages. ASO4 concentrations range from
1 µg m-3 (Buenos Aires, summer) to 17 µg m-3
(Kanpur, dry season). The fraction of sulfate in PM2.5 exhibits much
weaker spatial variation (10–30 %) as increases in ASO4 coincide with
increases in total PM2.5. Hence, locations with enhanced sulfate tend to
have enhancements in other aerosol components.

CM concentrations span an order of magnitude from 1.0 µg m-3
(Atlanta) to 16 µg m-3 (Beijing). The fraction of CM in
PM2.5 exhibits pronounced variation (5–25 %). Except during dust
storms, CM does not show clear patterns of temporal or regional variation.
This could be explained by non-seasonal road dust, which may account for over
80 % of CM in regions with heavy urban traffic (Huang et al., 2015).

We used Zn : Al ratios to assess the relative importance of local road dust
(cf. Table 3). Aluminum is mostly natural in origin (Zhang et al., 2006),
whereas Zn is primarily from tire wear (Begum et al., 2010; Councell et al.,
2004). For example, ratios are above 3 for Dhaka and Hanoi, but less than 0.3
for Mammoth Cave and the South Dekalb site (Atlanta). In fine-mode aerosols, the
ratio tends to be highest in large cities distant from natural CM. In
coarse-mode aerosols, a low Zn : Al ratio (< 0.1) indicates the aerosol CM
component is dominated by regional dust.

RM as inferred from mass reconstruction of inorganic compounds, PBW, and
total filter-weighed mass is implicitly treated as the organic aerosol mass
fraction. In terms of relative composition, RM spans a factor of 2, from
30 % mass in Buenos Aires to almost 60 % in Kanpur. Temporal changes in
RM tend to coincide with increases in ASO4, with an all-site
r2= 0.92. Although RM, as defined here, is not fully independent
from measured ASO4, correlations between these two mass fractions imply
related sources.

We interpret the abundance of water-soluble K relative to Al as an indicator
of wood smoke (e.g. Munchak et al., 2011). K : Al ratios averaged over each
site range from < 2 (Mammoth Cave, Atlanta) to 16 (Kanpur), where
combustion activity is apparent. Singapore was downwind of significant
Indonesian forest fire smoke during its sampling period of
August–November 2015, averaging to K : Al = 13. The correlation between
K : Al and RM across all SPARTAN sites is r2=0.73, supporting the
attribution of RM as mostly organic.

Across all sites, coarse- and fine-mode mass fractions are approximately equal
(0.50), with fractions ranging from below 0.40 (Hanoi, Buenos Aires, Manila) to above 0.55 (e.g. Bandung, Kanpur, Atlanta, Mammoth Cave). The two
size modes can be temporally correlated per site, though sometimes weakly,
from r2=0.15 (Hanoi) to r2=0.76 (Rehovot). We observe strong
temporal correlations between sulfate and ammonium in PM2.5 (r2= 0.72–0.99). Nitrate and ammonium are less consistently related
(Table 3), ranging from higher values in Singapore (r2=0.66), Kanpur
(r2=0.58), Beijing (r2=0.28), to weaker values in Ilorin and
Manila (r2<0.1). The strength of correlations with ammonium could be
influenced by excess ammonium relative to sulfate. The NH4+/[SO42-] ratio in PM2.5 is
2.6 in Kanpur and 1.3 in Ilorin.

Collocation overview

We compare SPARTAN PM2.5 speciation with previous studies available from
the literature and focus on collocated relative PM2.5 composition of
major components within the last 10 years. TEO is omitted due to lack of
significant mass contribution. Aerosol water content is also omitted as it
was not directly measured in any of the collocation studies. If not provided,
CM is treated as defined in Sect. 4.5 where possible. Organic mass (OM) to
organic carbon (OC) ratios are from Philip et al.
(2014b) with
updates from Canagaratna et al.
(2015).

Figure 3 provides an overview of the comparison studies organized by SPARTAN
data availability. Only sampling at Mammoth Cave was temporally
coincident with the comparison data. SPARTAN compositional information is
generally consistent with previous studies, considering inter-annual chemical
variation and measurement uncertainty. For example, both SPARTAN and
comparative studies find that PM2.5 is composed of between 10 and 30 %
ASO4 and 5–20 % CM for sampled sites. SPARTAN EBC mass fraction
generally matches within 5 percentage points of collocated studies, except
for Bandung and Kanpur. SPARTAN and prior studies find that ANO3 is
usually a small fraction of total mass, except at Beijing and Kanpur
(7–8 %) due to their high agricultural and industrial activity. All
studies find that sea salt is below 3 % of total mass. SPARTAN-derived RM
has potentially the largest potential error, yet typically is consistent with
the combined organic and unknown masses of other studies. This offers further
evidence that SPARTAN measurements of RM are predominantly organic in nature.

Individual site characteristics

Below, we discuss each site in more detail. We also examine how our chemical
composition from a global array of sites relates to local anthropogenic
activities and surrounding area. References to land type at specific sites
are derived from Latham et al. (2014), unless otherwise indicated. The number
of filters is given in parentheses.

Beijing, China (n=114)

Beijing has attracted considerable attention for its air pollution (Chen et
al., 2013). Agricultural areas to the west and the Gobi Desert to the north
surround the city's 19 million dwellers. The SPARTAN air sampler is located
on the Tsinghua University campus, 15 km northwest of the downtown centre.
This is our longest-running site, with 2.5 years of near-continuous sampling.
It reports the third-highest PM2.5, at 69 µg m-3, the
third-highest ASO4 (12 µg m-3), and the highest CM
(16 µg m-3) of all sites. The significant ANO3
(5.5 µg m-3) reflects significant urban NOx near
agricultural NH3 sources. ANO3 values were highest during winter,
as expected from ammonium-nitrate thermodynamics. A high CM component in the
springtime reflects regional, natural CM sources. The mean PM2.5 Zn : Al
ratio is lower than in other large cities (0.51) likely due to a larger
fraction of natural dust sources and the sampling location in the northwest
quadrant of the city, upwind of many traffic sources. The lowest coarse-mode
Zn : Al mass ratios are observed in April 2014 (0.07) and April 2015 (0.06)
during the annual yellow dust storm season. This is balanced by urban dust
sources throughout the year, in agreement with Lin et al. (2015) who found
evidence of high CM in industrial areas of Beijing.

The Beijing comparison showed that relative masses in Beijing compare well with
previous studies. SPARTAN ASO4 (19 %) is close to Yang et al. (2011)
(17 %) and Oanh et al. (2006) (20 %), and the RM of 37 % is similar to
combined OM (33 and 29 %) and unknown fractions (10 and 24 %) of
comparison studies. SPARTAN ANO3 concentrations (8.5 %) are relatively
higher than for most other locations, though lower than in either previous
study (11–12 %), possibly due to different sampling periods. CM is greater
than in Yang et al. (2011) (25 % vs. 19 %), and significantly higher than
in Oanh et al. (2006) (5 %), potentially due to a difference in
definitions.

Bandung, Indonesia (n=77)

Bandung is located inland on western Java surrounded by a volcanic mountain
range and agriculture (e.g. tea plantations). The sampler is located on the
Institute of Technology Bandung campus, 5 km north of the city centre.
Almost 2 years of sampling have resulted in a mean PM2.5 concentration
of 31 µg m-3. Sea salt is low at this elevated (826 m)
inland site. ANO3 and CM levels are also low, but RM is moderately high
compared with other sites, at 55 %. This could be explained by large
amounts of vegetative burning; organic PM2.5 mass fractions can rise
above 70 % during combustion episodes (Fujii et al., 2014). Volcanic sources
of sulfur, in addition to industrial sources, may explain the relatively higher
ASO4 compared with Manila or Dhaka (Lestari and Mauliadi, 2009). Influxes of volcanic dust from the Sinabang
volcano from August to September 2014 (2000 km northwest of Bandung) could
explain why coarse-mode Zn : Al ratios drop to 0.09 for this period
compared to the annual mean of 0.21.

The Bandung collocation took place in a volcanically active area, so that
composition, in particular ASO4, differs due to naturally variable
circumstances. SPARTAN ASO4 (21 %) is higher than the 4 % fraction
reported by Lestari and Mauliadi (2009), but is identical with measurements
by Oanh et al. (2006). SPARTAN EBC (13 %) is less than either previous
study (19 and 25 %) and the more recent analysis of 19 % BC (Santoso
et al., 2013). SPARTAN ANO3 is 2 %, by mass, lower than measured by
Oanh et al. (2006) (13 %) but similar to Lestari and Mauliadi (2009). Both
of the earlier studies show lower RM fractions (36 and 42 %) compared with
54 % RM in this study.

Manila, Philippines (n=63)

Manila is a coastal city located in Manila Bay, adjacent to the South China
Sea and surrounded by mountains. The sampling station, located at the Manila
Observatory, is about 40 m higher in altitude than the central city. The
PM2.5 concentrations at the observatory (18 µg m-3) are
expected to be lower than in the main city, but still influenced by vehicular
traffic, fuel combustion, and industry (Cohen et al., 2009). Compared to the all-site
average, the CM fraction in Manila is typical (11 %), but equivalent black
carbon is twice as great (25 %). The high EBC agrees with previous
observations, attributable to a relatively high use of diesel engines (Cohen
et al., 2002).

During the Manila collocation, it was found that SPARTAN fractions of ASO4 and EBC are
similar to Cohen et al. (2009). Our RM (43 %) is lower than OM (57 %),
whereas SPARTAN CM was greater than Cohen et al. (2009). These differences
could reflect sampling differences, or emission changes over the last decade.

Dhaka, Bangladesh (n=41)

Dhaka is a densely populated city (17 000 persons km-2) in a densely
populated country (1100 persons km-2). The sampler is situated in the
heart of downtown Dhaka, on the University of Dhaka rooftop, and is
influenced by air masses from the Indo-Gangetic Plain (Begum et al., 2012).
More than half the country is used for agricultural purposes (Ahmed, 2014).
Local contributing PM2.5 sources include coal and biomass burning, and
heavy road traffic combustion products and dust (Begum et al., 2010, 2012).
PM2.5 concentrations are the fourth-highest of any SPARTAN site, at
52 µg m-3. Dhaka has the second-highest absolute EBC of any
site, at 8.4 µg m-3, which can be explained by the abundance
of truck diesel engines (Begum et al., 2012). We estimate 41 % of
PM2.5 in Dhaka is RM. Crop or bush burning on both local and regional
scales contribute significantly to organics (Begum et al., 2012). The high
mean PM2.5 Zn : Al ratio of 3.4 reflects a large contribution from
urban traffic.

Ilorin, Nigeria (n=40)

Ilorin is located in a rural area with low-level agriculture and shrub
vegetation. The sampler is sited on the university campus, 15 km east of the
city of 500 000 people. Aerosol loadings have seasonal cycles from
agricultural burning events and dust storms (Generoso et al., 2003). The RM
accounted for two-thirds of total PM2.5 mass, among the largest,
influenced by biomass burning. There is evidence of biomass burning in the
PM2.5 peak in late spring 2014, and again in 2015. Lower ASO4
(12 %) compared to other SPARTAN sites reflects the sparse surrounding
industry. CM levels are comparable to other locations, except during dust
storms. During a dust storm (between 14 April and 2 May 2015), CM increased to
two-thirds of PM2.5 mass. The PMc Zn : Al ratio during the
storm decreased to 0.01 vs. 0.25 during non-storm days.

Kanpur, India (n=33)

Kanpur is a city of 2.5 million people. The sampler is located at the IIT
Kanpur campus airstrip, about 10 km northwest of the city. The city lies in
the Indo-Gangetic Plain, where massive river floodplains are used for
agricultural and industrial activity (Ram et al., 2012). We sampled
December 2013–May 2014, and September–November 2014, capturing one dry
season. SPARTAN-measured PM2.5 for this period was
99 µg m-3, the highest of any SPARTAN site, of which 59 %
is RM, 19 % ASO4, and 7.4 % ANO3. The absolute values of all
three components are also the highest among those measured. Molar
[NH4+] : [SO42-] ratios are higher in Kanpur (2.6) than
elsewhere. High background ammonia has been observed in the region from
satellite (e.g. Clarisse et al., 2009) which could explain the high levels of
ANO3. Wood smoke is apparent from the high K : Al ratio (16),
associated with organic matter burning during winter dry months. We detected
significant Zn concentrations (Zn : Al = 1.0), which is in agreement
with Misra et al. (2014) observations of a tripling of zinc during
anthropogenic sourced dust.

During the Kanpur collocation, relative fractions among the major species CM,
sea salt, ASO4, and ANO3 all matched well with previous studies
(Behera and Sharma, 2010; Chakraborty et al., 2015; Ram et al., 2012) that
also sampled during winter dry seasons. Chakraborty et al. (2015) measured
70 % organic mass composition and found a combined mass of 28 % for
ASO4+ ANO3 compared to SPARTAN mass (26 %). SPARTAN ASO4
(19 %) compares well to 13 % of Ram et al. (2012) and 18 % for Behera
and Sharma (2010), and ANO3 (7.4 %) is close to previous values
(6.1 and 6.6 %). By comparison, SPARTAN slightly overestimates EBC by
4–6 %. SPARTAN CM (4.8 %) is lower than Behera and Sharma (2010)
(10 %). Notably, the combined OM plus unknown fractions from these previous
two studies account for almost two-thirds of aerosol mass, 58 % for Behera
and Sharma (2010) and 63 % for Ram et al. (2012), similar to our 59 % RM
estimate. SPARTAN PM2.5 concentrations, as well as RM, reach a maximum
during the month of December. This is consistent with recent work (Villalobos
et al., 2015), who attribute this increase to agricultural burning and
stagnant air.

Buenos Aires, Argentina (n=31)

Buenos Aires has a metropolitan population of 12 million. SPARTAN instruments
are located on the urban CITEDEF campus 20 km west of the central downtown.
The megacity, the southernmost in our study, is surrounded by grassland and
farming on the west and the Atlantic Ocean on the east. The latter explains
the relatively high proportion (6 %) of sea salt. Total PM2.5
(10 µg m-3) and relative RM (31 %) are low compared with
other large metropolitan areas, likely influenced by clean maritime air. In
addition to sea salt and natural CM, the contribution of EBC is 17 %, which
could reflect significant local truck diesel combustion (Jasan et al., 2009).

Rehovot, Israel (n=30)

Rehovot is located on a four-story rooftop on the Weizmann Institute campus,
11 km from the Mediterranean Sea and 20 km south of Tel Aviv. The city is
surrounded by semi-arid, mixed-use cropland, and the region experiences
occasional Saharan desert dust outbreaks. Typical PM2.5 concentrations
are low (16 µg m-3), with the composition in Rehovot
consisting of 29 % ASO4, and 20 % CM. The RM fraction is smaller in
Rehovot (16 % total PM2.5 mass) than at other SPARTAN sites. Aerosol
sources in Israel include agriculture, desert dust, traffic, and coal-based
power plants (Graham et al., 2004). Relative sodium concentrations are high
in Rehovot (4 %), similar to Buenos Aires and Ilorin, and may include a
contribution from dust.

During the Lag Ba'Omer festival, we measured high ASO4 concentrations on
7–18 May 2015, during which time a large number of bonfires were lit nearby.
During the festival, over 75 % of total aerosol mass came from ASO4
and ANO3, leading to a brief doubling of the hygroscopic parameter
κv. We observed a K : Al ratio of 38 for 6 May during the
festival, the highest for any single filter.

A Saharan dust storm provided the opportunity to measure a severe dust
storm in Rehovot from a filter sampling on 4–13 February 2015. The coarse
filter Zn : Al ratio dropped to 0.02 during the Saharan dust storm from the
typical value of 0.3. On the coarse filter, we obtained an absolute CM mass of
950 µg, which accounts for half of the collected mass during the
storm. A total of 13 % of dust storm PMc is combined sea salt, ANO3,
and ASO4, leaving 35 % RM. Although this RM fraction may imply an
incomplete CM extraction, it is possible that a significant portion of desert
dust carries adsorbed organic material (Falkovich et al., 2004).

Mammoth Cave National Park, US (n=19)

The Mammoth Cave sampling site straddles national park (NP) mountainous terrain to
the north and east, with farmland to the south and west. It is about 35 km
from the closest town, Bowling Green, KY, with about 50 000 residents.
Sources of PM are expected to be non-local, hence we consider it our
background site.

Atlanta represents a major urban area in a developed country. The temporary
SPARTAN site was located at the South Dekalb supersite 15 km east of
downtown Atlanta. Air sampling was performed for a 4-month period spanning
winter to spring 2014. Over the past 10 years, significant decreases in
PM2.5 have been observed here and across the eastern United States (Boys
et al., 2014). The surrounding region is tree-covered or agricultural.

Singapore is a densely populated coastal city-state of
7770 people km-2. The sampler is located on a rooftop at the National
University of Singapore (NUS), near the centre of the city. Transportation is
of mixed use, including taxis, rail, and bicycles, which may help explain the
relatively low EBC and CM of 3 %. Despite this, the Zn : Al ratio remains
high at 1.5, implying a dominant traffic-based contribution to CM. SPARTAN
instruments have observed significant biomass burning downwind from
Indonesia, causing an increase in absolute PM2.5 from 32 in August to
120 µg m-3 in September 2015, as well as an increase in RM
from 44 to 62 %. The K : Al ratio steadily increased during this same
period, from 7.2 (24 July–2 August 2015) to 17–24
(11 August–25 September).

Hanoi, Vietnam (n=10)

Hanoi is an inland megacity surrounded by grassland and agriculture. The
sampler itself is on a building rooftop at the Vietnam Academy of Science and
Technology, 5 km northwest of the city centre. Motorbikes are the main forms
of transportation downtown and the primary source of mobile-based PM2.5
(Vu Van et al., 2013). In Hanoi, the PM2.5 Zn : Al ratio was 3.7,
also the highest of any SPARTAN site, indicative of significant traffic and
tire wear.

Pretoria is a high-altitude city (1300 m) surrounded by arid, low-intensity
agriculture and extensive grasslands. The SPARTAN sampler is located on a
10 m CSIR building rooftop 12 km east of downtown area (population 700 000).
Preliminary measurements of the Southern Hemisphere springtime show absolute
PM2.5 concentrations to be low, at 6.4 µg m-3. There are
significant fractions of CM (22 %) and EBC (22 %), and low RM (14 %).
The PM2.5 Zn : Al ratio (0.69) indicates vehicle traffic contributes
to CM.

Refining estimates of dry hourly PM2.5 using
κv

Our assessment of PM2.5 hygroscopicity is determined by site-specific
chemical composition. We then use the time-varying hygroscopicity to refine
the PM2.5 values inferred from nephelometer scatter.

Relating PM2.5 composition to κv

The outer pie charts of Fig. 2 show the site mean hygroscopic growth
constant κv, surrounded by the water contributions at 35 %
RH. The major contributors to PBW are ASO4, ANO3, RM, and sea salt,
as inferred from the values listed in Table 2 and weighted by composition as
in Eq. (5). ASO4 and RM contribute similarly to total aerosol water,
whereas ANO3 contributes less to PM2.5 hygroscopicity due to its
smaller mass. The contribution of sea salt to hygroscopicity can be
significant, and makes a dominant contribution in both Rehovot and Buenos
Aires.

The parameter κv, when averaged across all sites, is 0.20,
matching the generic estimate κv,tot=0.2 applied in the
initial SPARTAN study
(Snider et al., 2015). Recently Brock et al. (2016)
estimate κv values between 0.15 and 0.25 for ambient
aerosols with 50 % organic composition at sub-saturated humidity. The local
SPARTAN value in Atlanta (0.17) is consistent with the value of
0.16 ± 0.07 by Padró et al. (2012) in Atlanta. We found significant
long-term differences in κv,tot between cities, from 0.15 in
Ilorin to 0.28 in Rehovot, and differences between filters at single sites
(σ∼ 0.05). There is little correlation of κv,tot
with changes in mass (r2=0.01). However, there are significant changes
in κv,tot due to seasonality and specific events (e.g. dust
storms, fires). In Beijing, aerosol hygroscopicity was 50 % higher in mid-summer
(August) due to increased sulfate, and in late winter (March) due to a
relative increase in sea salt. A summertime sulfate peak also agrees with
observations by Yang et al. (2011). Table 3 shows the site-specific PBW in
PM2.5. At RH = 35 %, PBW ranges from 0.6–6 µg m-3,
comparable in absolute values to EBC. Above 80 % RH PBW will account for
more than half of aerosol mass. Accounting for this water component in
nephelometer scatter motivates the following section.

Relating nephelometer scatter to dry (RH = 35 %) PM2.5

We apply a temporally resolved, site-specific κv to refine
our relationship between total nephelometer scatter and PM2.5. We
calculate a 45-day running mean aerosol volume-weighted κv
at each SPARTAN site. We then use the hygroscopic growth factors to estimate
dry hourly PM2.5 from hourly nephelometer measurements of ambient
scatter and hourly measured RH. Appendix A2 describes the procedure in more
detail.

Left: hourly PM2.5 estimated from SPARTAN overlaid with a
MetOne BAM-1020 (June–August 2014) at the Beijing US embassy (15 km away).
Right: 24 h SPARTAN PM2.5 compared with BAM for the year 2014.
Reduced major axis (RMA) slope and Pearson correlations for PM2.5 are
given in inset.

We compared our hourly PM2.5 in Beijing with PM2.5 measurements
from a beta attenuation monitor (BAM, MetOne) at the US embassy, located
15 km away. The BAM instrument contains a drying column with a 35 %
humidity set point. The left panel of Fig. 4 shows the time series of hourly
dry PM2.5 concentrations predicted by SPARTAN during the summer.
Pronounced temporal variation is apparent, with PM2.5 concentrations
varying by more than an order of magnitude. A high degree of consistency is
found with the BAM (r2=0.67). The exclusion of water uptake in hourly
PM2.5 estimates (by setting all
κv to 0) decreased
hourly correlations slightly to r2=0.62. The average humidity in
Beijing was 47 % for the measurement period, corresponding to a mean 17 %
volume contribution by water (κv=0.19). Hygroscopic growth
should play a more significant role under more humid conditions (e.g. Manila
and Dhaka).

The right panel in Fig. 4 shows daily-averaged PM2.5 (n=148). In
2014, there were 3167 coincidentally available hours with which to compare.
The coefficient of variation for averaged 24 h measurements remained high
(r2=0.70). There was a mean offset of 10 µg m-3.
However, the slope is near unity (0.98), suggesting excellent proportionality
between our nephelometer and the BAM instrument for PM2.5 concentrations
below 200 µg m-3. Above this concentration, nephelometer
signals become non-linear. The agreement remained similar for hourly values
(r2=0.67).

Conclusions

We have established a multi-country network where continuous monitoring with
a three-wavelength nephelometer is combined with a single multi-day composite
filter sample to provide information on PM2.5. Long-term average
aerosol composition is inferred from the filters, including equivalent black
carbon, sea salt, crustal material, ammoniated sulfate, and ammonium
nitrate. This composition information was applied to calculate aerosol
hygroscopicity, and in turn the relation between aerosol scatter at ambient
and controlled RH. These data provide a consistent set of compositional
measurements from 13 sites in 11 countries.

Crustal material concentrations ranged from 1 µg m-3
(Atlanta) to 16 µg m-3 (Beijing). Measuring Zn : Al ratios
in PM2.5 was an effective way to determine anthropogenic contribution to
crustal material. Ratios larger than 0.5 identified sites with significant
road dust contributions (e.g. in Hanoi, Dhaka, Manila, and Kanpur). Some
locations, such as Beijing and Buenos Aires, had both high anthropogenic and
natural crustal material. Low coarse Zn : Al ratios were apparent during
natural dust storms. Anthropogenic crustal material is an aerosol component
neglected by most global models and which may deserve more attention.

Potassium is a known marker for wood smoke. Enhanced K : Al ratios were
found in Singapore downwind of Indonesian forest fires, in Kanpur during the
winter dry season from agricultural burning, and in Rehovot during a bonfire
festival. Furthermore, these ratios were correlated with RM concentrations
(r2=0.73), supporting the attribution of RM as mostly organic.

SPARTAN measurements generally agree well with previous collocated studies.
SPARTAN sulfate fractions are within 4 % of fractions measured at 8 of
the 10 collocated, though temporally non-coincident, studies. Dedicated
contemporaneous collocation with IMPROVE at Mammoth Cave yielded a high
degree of consistency with daily sulfate (r2=0.86, slope = 1.03),
daily PM2.5 (r2=0.76, slope = 1.12), and mean fractions for
all major PM2.5 components within 2 %. Crustal material is typically
consistent with the previous measurements, at 5–15 % composition. SPARTAN
equivalent black carbon ranged broadly, from 3 % (Singapore) to 25 %
(Manila), and matched within a few percent of most previous works. Ammonium
nitrate (4 %) generally matched other sites, though it was sometimes lower,
as in Beijing and Atlanta. Sea salt was consistently low, as found in
previous measurements. Sea salt fractions were highest in Buenos Aires and
Rehovot (6 %), reflecting natural coastal aerosols. SPARTAN residual matter
is consistent with the combined organic and unknown masses. Comparing with
collocated measurements supports the expectation that most of the RM is
partially organic. Residual matter could also include unaccounted-for
particle-bound water, measurement error, and possibly unmeasured inorganic
materials.

We calculated the hygroscopic constant κv for individual
PM2.5 filters to estimate water at variable humidity, and to infer wet
and water-free residual matter. Based on a range of literature, we treated
residual matter as mostly organic, with constant κv,RM= 0.1.
Residual matter and ammoniated sulfate largely determined overall water
uptake in aerosols. These individual species, along with sea salt and
ammonium nitrate, resulted in a mean mixed hygroscopic constant of 0.20,
implying that for many sites, water content above 80 % RH will account for
more than half of aerosol mass. For cleanroom conditions of low humidity
(35 % RH), mean water composition was estimated to be 7 % by mass.

Water retention calculations allow for volumetric fluctuation estimates of
aerosol water at variable RH. We subtracted the water component to predict
dry nephelometer scatter as a function of time, anchored to filter masses at
35 % RH. For Beijing, we assessed the consistency of SPARTAN predictions of
hourly PM2.5 values with BAM measurements taken 15 km away, and found
temporal consistency (r2= 0.67), with a slope near unity (0.98). The
explained variance decreased to r2= 0.62 when setting
κv= 0. This comparison tested both SPARTAN instrumentation
and our treatment of aerosol water uptake.

These measurements provide chemical and physical data for future research on
PM2.5. Collocation with sun photometer measurements of AOD connects
satellite observations to ground-based measurements and provides information
needed to evaluate chemical transport model simulations of the PM2.5 to
AOD ratio. As sampling expands, SPARTAN will provide long-term data on fine
aerosol variability from around the world. Ongoing work includes an analysis
of trace metal concentrations and interpreting SPARTAN measurements with a
chemical transport model. The data are freely available as a public good at
www.spartan-network.org. We welcome expressions of interest to join
this grass-roots network.

Data availability

SPARTAN aerosol mass and composition data are freely available at
www.spartan-network.org. Hourly PM2.5
data from Beijing is provided by the U.S. Department of State Air Quality Monitoring Program. State Air data are not fully validated and is used here only for comparative purposes with
SPARTAN. Hourly PM2.5 data from the U.S. Embassy in Beijing is provided by the U.S. Department of State Air Quality Monitoring Program.
State Air PM2.5 data is not fully validated, and used solely for comparative purposes
http://www.stateair.net/web/mission/1/.

Dry aerosol scatter (bsp,dry) is related to relative
humidity (RH) by
bsp,dry=bsp(RH)fv(RH).
Changes in scatter are also proportional to mass
(Chow et al., 2006; Wang et al., 2010) as
bsp,dry=αPM2.5,dry,
where α (m2 g-1) is the mass scattering efficiency and a
function of aerosol size distribution, effective radius, and dry
composition. In this study, we treat composition, density, and size
distribution as constant over each of our 9-day intermittent sampling
periods so that α≈<α>9d. Under this assumption the predicted mass changes in low humidity
(35 % RH) are proportional to water-free aerosol scatter:
PM2.5,dry=[<PM2.5,dry>]bsp,dry<bsp,dry>,
where <> indicates 9-day averages. The explicit
compensation for aerosol water is then
[PM2.5,dry]=<[PM2.5,dry]><bsp(RH)/fvRH>⋅bsp(RH)fv(RH),
where [] indicates concentration in µg m-3. Uncertainties are
a function of replicate weighing measurements (±4 µg), flow
volume (±10 %), %RH (±2.5), aerosol scatter (±5 %), and κv (±0.05).
δ[PM2.5,h][PM2.5,h]2≈δPM2.5PM2.52+δVV2+δbspbsp2+δfvfv2,
where
δfvfv2=fv-12fv2δκκ2+δRHRH⋅(100-RH)2.

The average relative 2σ PM2.5 uncertainty was 26 % for dry
hourly predictions, increasing with higher RH cutoffs. A cutoff of RH =
80 % has been applied to our data, above which hygroscopic uncertainties,
as well as total water mass, dominate.

Acknowledgements

SPARTAN is an IGAC-endorsed activity (www.igacproject.org). The Natural
Sciences and Engineering Research Council (NSERC) of Canada supported this
work. We are grateful to many who have offered helpful comments and advice on
the creation of this network including Jay Al-Saadi, Ross Anderson, Kalpana
Balakrishnan, Len Barrie, Sundar Christopher, Matthew Cooper, Jim Crawford,
Doug Dockery, Jill Engel-Cox, Greg Evans, Markus Fiebig, Allan Goldstein,
Judy Guernsey, Ray Hoff, Rudy Husar, Mike Jerrett, Michaela Kendall, Rich
Kleidman, Petros Koutrakis, Glynis Lough, Doreen Neil, John Ogren, Norm
O'Neil, Jeff Pierce, Thomas Holzer-Popp, Ana Prados, Lorraine Remer, Sylvia
Richardson, and Frank Speizer. Data collection in Rehovot was supported in part
by the Environmental Health Fund (Israel) and the Weizmann Institute. Partial
support for the ITB site was under the grant HIBAH WCU-ITB. The site at IIT
Kanpur is supported in part by National Academy of Sciences and USAID. The
views expressed here are of authors and do not necessarily reflect those of
NAS or USAID. The Singapore site is supported by the Singapore National
Research Foundation (NRF) through the Singapore-MIT Alliance for Research and
Technology (SMART), Center for Environmental Sensing and
Modeling.Edited by: W. Maenhaut
Reviewed by: three anonymous referees